Metabolic imaging in living plants: A promising field for chemical exchange saturation transfer (CEST) MRI

Magnetic resonance imaging (MRI) is a versatile technique in the biomedical field, but its application to the study of plant metabolism in vivo remains challenging because of magnetic susceptibility problems. In this study, we report the establishment of chemical exchange saturation transfer (CEST) for plant MRI. This method enables noninvasive access to the metabolism of sugars and amino acids in complex sink organs (seeds, fruits, taproots, and tubers) of major crops (maize, barley, pea, potato, sugar beet, and sugarcane). Because of its high signal detection sensitivity and low susceptibility to magnetic field inhomogeneities, CEST analyzes heterogeneous botanical samples inaccessible to conventional magnetic resonance spectroscopy. The approach provides unprecedented insight into the dynamics and distribution of sugars and amino acids in intact, living plant tissue. The method is validated by chemical shift imaging, infrared microscopy, chromatography, and mass spectrometry. CEST is a versatile and promising tool for studying plant metabolism in vivo, with many applications in plant science and crop improvement.


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Supplementary Texts S1 to S5 Figs.S1 to S11 Table S1 Legend for movie S1 References Other Supplementary Material for this manuscript includes the following:

Supplementary Text 1 Performing a CEST experiment
A CEST experiment includes the acquisition of many MR images, each prepared with a different saturation frequency (see Fig. S1D).In our experiments the preparation comprises one single RF pulse with constant amplitude (block pulse; see Suppl.Text 2 for more details) followed by the signal acquisition.For that, we used a conventional Cartesian fast spin echo technique (see Methods).Plotting the saturation signal (for each pixel) as a function of the saturation frequency gives the so-called Z-or CEST spectrum (Fig. 1D).The frequency is stated as the relative shift Δω to the water frequency in parts per million [ppm].The signal S(Δω) is normalized to a reference signal Sref without or alternatively with far off-resonant saturation.The Z-spectrum exhibits a peak around 0 ppm due to direct water saturation.The direct water saturation can interfere with CEST effects, especially with those of sugars because their exchanging hydroxyl protons have only a small chemical shift to water of around 1 ppm (27).To eliminate the effect of direct saturation, different evaluation procedures have been developed (62)(63)(64).The simplest and most frequently utilized method, which we also applied in this work, is the calculation of the asymmetry spectrum MTRasy (65) MTR asy (Δω) = S(−Δω) − S(Δω) S ref

(S1)
For calculating this metric, the exact water frequency (0 ppm) is required to choose the two corresponding signals on the opposite sites at ±Δω.This is of crucial importance because small deviations can already lead to large errors in the asymmetry spectrum, especially for signal close to the water frequency like for sugars at around 1ppm (see Fig. S4).An established method to determine the water frequency (B0 map) is the so-called WASSR approach (59).A WASSR spectrum is basically a Z-spectrum with a short and low saturation.In that case, the CEST effect is negligible and only direct water saturation is measured.Then, the center (= minimum) of the WASSR spectrum corresponds to the desired water frequency.

Choice of the CEST saturation parameters
In this work, we used continuous wave (cw) CEST: The saturation of our CEST experiments consisted of one rectangular (block shaped) radiofrequency pulse of duration tp, amplitude B1 and frequency offset Δω.For the acquisition of a full Z-spectrum, the measurement is repeated for different frequency offsets Δω.The CEST effect depends on the two saturation parameters tp (saturation time) and B1 (saturation power).
Although the saturation parameters are given in the method section, we would like to explain why this choice makes sense.For this purpose, we performed CEST measurements on a young pea using different saturation parameters.The outcome is shown in Fig. S2, where measured Z-and asymmetry MTRasy spectra from the liquid endosperm of the pea are presented for various saturation parameters.Each asymmetry MTRasy spectrum shows two peaks, one at about 1 ppm due to the exchanging hydroxyl protons, interpreted as sugar signal, the other nearly 3 ppm due to the exchanging amino protons, interpreted as amino acid signal.If the saturation power is too low, like 1 µT, there is only a slight CEST effect and only small peaks.If the saturation power is too high, the exchanging peaks and the water peak (direct water excitation) become broader and can no longer be easily separated from each other (Fig. S2A).
The CEST effect rises with increasing saturation time (see Fig. S2B) until it reaches a steady state for a sufficiently long saturation time.This is the case because the accumulation of saturation due to multiple exchange is limited/reduced by T1 relaxation of the (saturated) water protons.The CEST effect is therefore influenced by T1 relaxation of the measured substance/tissue.As the influence of T1 on the CEST effect increases with longer saturation time (due to the fact that an extended saturation time leads to a prolonged time for T1 relaxation), our strategy was to favor shorter saturation times.In this particular case of the young pea, appropriate parameters were B1=2 µT and tp=300 ms.

Supplementary Text 3 Spatial resolution of CSI and CEST images
In the following, we explain the reasons for the different spatial resolutions of CSI and CEST images.The resolution of an image is defined as the field of view (FOV) divided by the matrix size of the image.
CSI measurements have long measurement times if high spatial resolved images are acquired.For example, a CSI measurement on a young pea with an isotropic resolution of 100 µm took over 11 hours (10).One reason for this is that a spectrum is acquired for each voxel, which corresponds to an additional measurement dimension in addition to the spatial dimensions.MRI speaking, no (fast) read encoding can be used for image acquisition, but only (slow) phase encoding.On the other hand, CSI directly measures low metabolite signals compared to the water signal usually measured in MRI (as metabolites are less concentrated than water).Therefore, signal averaging is usually required to obtain a sufficient signal to noise ratio (SNR), which can increase the measurement time immensely.For this reason, CSI measurements tend to be performed at lower resolutions compared to MRI, such as our measurement of the young pea with resolution of 300 µm (see Fig. 1).However, lower resolutions correspond to larger voxels, which in turn makes the measurement more susceptible to magnetic field inhomogeneities.In addition, small acquisition matrices lead to an inconvenient point spread function: The point spread function now also exhibits side loops outside the nominal resolution (FOV divided by matrix size), which means that the signal of a voxel is contaminated by signals from neighboring voxels (66).
CEST, on the other hand, is an MRI method.This means that read encoding can be used for image acquisition, which significantly reduces the measurement time.Furthermore, less image averaging is usually required as no small metabolite signals are directly measured, but (saturated) water signal (note the accumulation effect due to multiple exchanges!).
In our work, we have achieved resolutions of up to 50 µm for CEST (see the measurement on the young pea).This is a typical spatial resolution for a MR microscopy measurement, whose resolution is generally in the range of 10 µm to 100 µm (67).The lower resolution limit is usually limited by the signal-to-noise-ratio (SNR), which decreases proportionally with the voxel volume.
As the SNR can be increased by longer (repeated) data acquisition, there is always a trade-off between measurement time and resolution.Additionally, microscopy measurements are only possible if optimized NMR devices are available: The measurements in this work were carried out on high-field devices (400 MHz or 500 MHz); furthermore, a 5 mm cryo sample head for the

Supplementary Text 4
Influence of magnet field inhomogeneities on CSI and CEST measurements CEST measurements are significantly less sensitive to magnetic field inhomogeneities compared to CSI.Since these inhomogeneities often occur in plant samples, this represents a decisive advantage of CEST over CSI.In the following, this will be demonstrated and explained using exemplary measurements on a pea at mid-developmental stage (see Fig. S3A).A distinction must be made between magnetic field inhomogeneities across the whole sample and magnetic field inhomogeneities within individual voxels.

Magnetic field shifts across the sample
The high water content in living plant tissue results in a strong dominance of water peaks over soluble metabolites in CSI spectra.In classical CSI approach, the water signal must be suppressed for quantitative analysis of metabolites.The most accepted method for water suppression is to use global (over the whole sample) frequency-selective saturation pulses.The success of the experiment depends to a large extent on the efficiency/accuracy of the water suppression.
Fig. S3A shows as an example the reference structural MR image and the corresponding sugar signal distribution measured by CSI of a pea sample (Fig. S3B).Excessive signal can be seen at the edge of the sample (arrowed in Fig. S3B).At these locations, the water signal appears to be insufficiently suppressed and overlaps the signals of the metabolites.The reason for this lies in global magnetic field inhomogeneities (very common in plants), which lead to different shifts of the resonance frequency across the sample.If the local resonance frequencies are strongly shifted (e.g.greater than the bandwidth of the saturation pulses), the water suppression aimed by global frequency-selective saturation pulses is not achieved and the metabolite signals cannot be detected separately.
We measured the field shifts (B0 map) using the WASSR method (59), to demonstrate strong magnet fields inhomogeneities within the sample (Fig. S3C).The frequency shift is shown in Hz.
Especially at locations with shifts of the water resonance to lower frequencies (e.g.seen in blue, Fig. S3C), the water signal is insufficiently saturated, leading to erroneous additional signal in the CSI sugar map (Fig. S3B).Such an artifact cannot be corrected by post-processing and represents a significant limitation of CSI for metabolite measurements in plant NMR.CEST spectra could also be affected by magnet field inhomogeneity leading to shifts of the CEST spectra in the frequency/ppm direction (Fig. S4A).This results in erroneous CEST signal maps (see Fig. S4C).However, it can be corrected based on a separately measured B0 map (e.g. using the WASSR method) and shifting the Z-spectra of each voxel based on the respective frequency from the B0 map.This ensures that the water peak of each Z spectrum is actually in the center at 0 ppm, so that a correct asymmetric analysis can now be performed (see Fig. S4B, D).The procedure can be easily performed in post-processing.Frequency shifts within the sample due to magnetic field inhomogeneities can therefore be corrected for CEST measurements.The WASSR measurements were always carried out with the same repetition times TR as the corresponding CEST measurements.And a large number of ppm-offsets was measured.Both led to relatively long measurements (usually similar in length to the CEST measurement itself).It should be noted here that a significant acceleration of the WASSR measurement time is possible by reducing TR and the number of ppm-offsets.The CEST measurements themselves can also be accelerated, particularly through shorter recovery times and faster readouts.These time optimizations should be made for 3D measurements at the latest, as mentioned in the discussion section.

Movie S1.
Dynamic imaging of sugars and amino acids via CEST within a growing barley caryopsis.

Figure S1 :
Analysis of liquid endosperm in developing pea seeds.(A, B) Relative levels of soluble sugars and free amino acids in dissected endosperm measured at distinct developmental stages by chromatography.(C, D) 3D model of a pea seed showing the orientation of the slide measured by MRI and shown in (D1-11).A selection of single CEST images with saturation at different frequencies (slice thickness 400 µm).Bar: 1 mm.Abbreviations: en, endosperm; sc, seed coat.

Supplementary
Figure S2: Measured Z-spectra and corresponding asymmetry spectra MTRasy of liquid endosperm of a young pea for different saturation parameters.(A) Z-spectra for different saturation powers B1 and saturation time tp=300 ms, and the corresponding asymmetry spectra MTRasy.(B) Z-spectra for different saturation times tp and saturation power B1=2 µT, and the corresponding asymmetry spectra MTRasy.

Supplementary Figure S3 :
Measurements on a pea at mid-developmental stage for explaining the influence of magnet field shifts on CSI.(A) Structural reference image of a slice (thickness 400 µm) through a pea.The blue circle indicates the position of the voxel whose Zspectrum is shown in Fig. S4A,B.The red (a) and blue (b) crosses show the positions of the voxels whose signals are plotted in Fig. S5A,C.(B) CSI map of sugar signal.Arrows indicate locations with high signals due to insufficient water suppression.(C) B0 map acquired by a WASSR measurement.